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Post-Secondary
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 991 - 1020 of 1035
On the application of Large Language Models for language teaching and assessment technology
Andrew Caines, Luca Benedetto, Shiva Taslimipoor, Christopher Davis, Yuan Gao, ¯istein Andersen, Zheng Yuan, Mark Elliott, Russell Moore, Christopher Bryant, Marek Rei, Helen Yannakoudakis, Andrew Mullooly, Diane Nicholls, Paula Buttery. (07/2023). arXiv. http://arxiv.org/pdf/2307.08393v1
A large language model-assisted education tool to provide feedback on open-ended responses
Jordan K. Matelsky, Felipe Parodi, Tony Liu, Richard D. Lange, Konrad P. Kording. (07/2023). arXiv. http://arxiv.org/pdf/2308.02439v1
GPT detectors are biased against non-native English writers
Weixin Liang, Mert Yuksekgonul, Yining Mao, Eric Wu, James Zou. (07/2023). ScienceDirect. https://www.sciencedirect.com/science/article/pii/S2666389923001307
GPTeach: Interactive TA Training with GPT-based Students
Julia M. Markel, Steven G. Opferman, James A. Landay, Chris Piech. (07/2023). ACM Digital Library. https://dl.acm.org/doi/10.1145/3573051.3593393
Promptly: Using Prompt Problems to Teach Learners How to Effectively Utilize AI Code Generators
Paul Denny, Juho Leinonen, Andrew Luxton-Reilly, Thezyrie Amarouche, Brent N. Reeves, James Prather, Brett A. Becker. (07/2023). arXiv. http://arxiv.org/pdf/2307.16364v1
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts
Rose E. Wang, Pawan Wirawarn, Noah Goodman, Dorottya Demszky. (06/2023). arXiv. http://arxiv.org/pdf/2306.09343v1
Assigning AI: Seven Approaches For Students With Prompts
Dr. Ethan Mollick, Dr. Lilach Mollick. (06/2023). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4475995
The effect of generative artificial intelligence (AI)-based tool use on students' computational thinking skills, programming self-efficacy and motivation
Ramazan Yilmaz, Fatma Gizem Karaoglan Yilmaz. (06/2023). Computers and Education, Artificial Intelligence. https://www.sciencedirect.com/science/article/pii/S2666920X23000267
Computing Education in the Era of Generative AI
Paul Denny, James Prather, Brett A. Becker, James Finnie-Ansley, Arto Hellas, Juho Leinonen, Andrew Luxton-Reilly, Brent N. Reeves, Eddie Antonio Santos, Sami Sarsa. (06/2023). arXiv. http://arxiv.org/pdf/2306.02608v1
Generative AI: Implications and Applications for Education
Anastasia Olga (Olnancy) Tzirides, Akash Saini, Gabriela Zapata, Duane Searsmith, Bill Cope, Mary Kalantzis, Vania Castro, Theodora Kourkoulou, John Jones, Rodrigo Abrantes da Silva, Jen Whiting, Nikoleta Polyxeni Kastania. (05/2023). arXiv. https://arxiv.org/pdf/2305.07605
Visualizing Self-Regulated Learner Profiles in Dashboards: Design Insights from Teachers
Paola Mejia-Domenzain, Eva Laini, Seyed Parsa Neshaei, Thiemo Wambsganss, Tanja Kaser. (05/2023). arXiv. http://arxiv.org/pdf/2305.16851v1
Enhancing Chemistry Learning with ChatGPT and Bing Chat as Agents-to-Think-With: A Comparative Case Study
Renato P. dos Santos. (05/2023). arXiv. http://arxiv.org/pdf/2305.11890v1
The Utility of Large Language Models and Generative AI for Education Research
Andrew Katz, Umair Shakir, Benjamin Chambers. (05/2023). arXiv. https://arxiv.org/pdf/2305.18125
Scalable Educational Question Generation with Pre-trained Language Models
Sahan Bulathwela, Hamze Muse and Emine Yilmaz. (05/2023). arXiv. http://arxiv.org/pdf/2305.07871v1
How Useful are Educational Questions Generated by Large Language Models?
Sabina Elkins, Ekaterina Kochmar, Iulian Serban, Jackie C.K. Cheung. (04/2023). arXiv. http://arxiv.org/pdf/2304.06638v1
Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models
Tung Phung, Jose Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Gustavo Soares. (04/2023). arXiv. http://arxiv.org/pdf/2302.04662v2
Comparing Code Explanations Created by Students and Large Language Models
Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, Seth Bernstein, Joanne Kim, Andrew Tran, Arto Hellas. (04/2023). arXiv. http://arxiv.org/pdf/2304.03938v1
ChatGPT or academic scientist? Distinguishing authorship with over 99% accuracy using off-the-shelf machine learning tools.
Heather Desaire, Aleesa E. Chua, Madeline Isom, Romana Jarosova, David Hua. (03/2023). arXiv. http://arxiv.org/pdf/2303.16352v1
ChatGPT for education and research: A review of benefits and risks
Sarin Sok, Kimkong Heng. (03/2023). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4378735
Could an Artificial-Intelligence agent pass an introductory physics course?
Gerd Kortemeyer. (02/2023). arXiv. http://arxiv.org/pdf/2301.12127v2
New Modes of Learning Enabled by AI Chatbots: Three Methods and Assignments
Dr. Ethan Mollick, Dr. Lilach Mollick. (12/2022). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4300783
Aligning Learners' Expectations and Performance by Learning Analytics System with a Predictive Model
Sasa Brdnik, Bostjan Sumak, Vili Podgorelec. (11/2022). arXiv. http://arxiv.org/pdf/2211.07729v1
A Review of Artificial Intelligence (AI) in Education during the Digital Era
Pongsakorn Limna, Somporch Jakwatanatham, Sutithep Siripipattanakul, Pichart Kaewpuang, Patcharavadee Sriboonruang. (07/2022). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4160798
Artificial Intelligence, Education, and Entrepreneurship
Michael Gofman, Zhao Jin. (07/2022). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3449440
Automatic Generation Of Programming Exercises And Code Explanations With Large Language Models
Sami Sarsa, Paul Denny, Juho Leinonen, Arto Hellas. (06/2022). arXiv. http://arxiv.org/pdf/2206.11861v2
